The overall goal of this research is to determine how conflicting visual and self-motion information modulates the responses of the postural control system in elderly adults and in individuals post-stroke. When visual field information does not match self-motion feedback, healthy elderly respond to combined visual, vestibular, and proprioceptive signals differently than young adults. Young adults incorporate frequency components of all inputs into their responses;elderly adults rely primarily on vision. We hypothesize that elderly adults and individuals post-stroke have increased sensory thresholds to complex multimodal stimuli which produces a greater reliance on predictive or on visual inputs making it more difficult for them to selectively respond to visual and physical destabilization. By combining the technology of a virtual environment with support surface translations we plan to manipulate the influence of visual inputs, somatosensory (i.e., proprioceptive and vestibular) inputs, and prediction to reveal the contribution of segmental inputs and higher order processing to the postural response. We plan to compare healthy young and elderly individuals with young and elderly individuals post-stroke in order to distinguish between the effects of age and CNS impairment. We will first explore whether subjects change their responses to particular sensory modalities over time. Then the head and trunk will be aligned in different positions with respect to visual and support surface motion to reveal how altering sensory and biomechanical orientations affects the response to visual motion signals. Lastly, we will examine how predictable and random visual inputs influence the response to random support surface inputs. Visual field dependence will be measured with a Rod and Frame test. We will employ novel methods of Principal Component Analysis and autoregressive modeling to distinguish between body mechanics and specified neural processes. These analyses should reveal how the selection of control pathways is determined by the task as well as further define response properties of the afferent pathways. Segmental and muscle response strategies will be examined through kinematic measures including center of pressure, center of mass displacement, and electromyography, and tested for significance with a MANOVA. Clarifying the relation between visual inputs and postural stabilization will identify functional situations that present a high probability for instability and falling. Results from the proposed studies can potentially be used for developing individually designed programs of therapeutic intervention.